Nilesh Jethwa

Using the data from pwcmoneytree.com and easy to use dashboard software we perform analytics on a huge dataset that spans 20 years of Venture capital investment data from 1995 onward. Having data that goes far into the history should give us enough to extract the necessary analytical juice out of it.

The year 2000 was definitely the peak for VC investment craziness. A whopping 105 Billions was pumped into startups and bringing them quickly for IPO. Ever since after the crash of 2000… Continue reading the original article

Lot of the entities have already paid the amount back to the government with interest and the government has made profits! Government has also lost money on lot of other organizations/companies that failed to repay back.

How has the interest in Big Data, Hadoop, Business Intelligence, Analytics and Dashboards changed over the years?

One easy way to gauge the interest is to measure how much news is generated for the related term and Google Trends allows you do that very easily.

After plugging all of the above terms in Google trends and further analysis leads to the following visualizations.

Aggregating the results by year

It is very amazing to see that the stream representing Dashboards has remained constant through out the years.

So does the stream for Analytics and Business Intelligence in general exihibit similar trend.

Analytics is kind of widening its mouth as we move forward and that is being helped by the combination of terms such as Hadoop + Big Data + Analytics being used almost together.

Now check the line chart below

Looks like the Trend for Dashboards define the lower bound and the trend for Business Intelligence define the upper bound. The trend for Hadoop started around first Quarter of 2007. The trend for Big Data started around third Quarter of 2008 and ever since they both are rapidly increasing. It remains to see whether they will cross “Business Intelligence” in terms of popularity of kind of merge and find a stable position somewhere in the middle.

Before Big Data and Hadoop came into picture the term “Analytics” exhibited a stable ground closer to dashboards but now the trend for Analytics seems to be following Big Data and Hadoop.

Let us take a deeper look into each week since 2004

Look at the downward spikes occuring around Christmas time. Nobody wants to hear about Big Data or Dashboards during holidays.

So the important question is “Why the DMCA takedown notices have increased?”

One important thing to note is sites like Stackoverflow encourage to replicate the content of the web page from where the original idea/algorithm or source code is copied from. To be honest it is a good thing because lot of times these referring sites become zombies and you don’t want to lose this knowledge. But could it be the case that such non-referenceable source codes end up in GitHub and hence causing the increase in the takedown notices as companies start discovering them?

For every dime there are dozen analytic companies. Everybody who provides a freaking dashboard is an analytic company. Anybody that merely mentions Google, Facebook, Hadoop etc in the same sentence is somehow into BigData. Haven’t you stumbled across company pages where they claim to be expert in analytics and big data but they want you to schedule a call with them. They don’t have any products or solutions to show case yet they are Big Data/analytics folks.

We thought the above visual would tell us what kind of logic did Mattermark used to rank the companies. As suspected, apparently we cannot reverse engineer it without some additional information about the companies.

After finishing our call with Bed Bugs , we decided to check out what the startup scene looks like. We used the data from seed-db to let our analytical juices flowing.

First we asked what is the top most program (duh!!) but by how much and who are next in the list and so on.

Like most Data scientists who believe in the power of simple bar graphs we used our first “chart weapon” of choice and here it is what it rendered.

Y Combinator is freaking huge like a dinasaur, infact very much resembles the grass eating Sauropods. In fact we had to create a chart that was 3000 pixels wide just to accommodate all.

See the resemblance between the chart and the Sauropod?

To get better perspective we rendered it in a Treemap as shown

Looking at the treemap, Y Combinator occupies more than the sum total of all the remaining accelerators. That is super amazing but the problem our charts were not coming up beautiful. YC is clearly the outlier and was causing us difficulty to understand the remainder startup ecosystem.

We said, lets cut off the head to dig deeper.

The moment we filtered out YC from our analysis, all of the regions became colorful and that was certainly a visual treat.

Now we could clearly see what are the other accelerators/programs that are roughly the same size.

For example,

TechStars Boulder and AngelPad are roughly the same

TechStars NYC, TechStars Boston and 500Startups are in the same club

Similarly DreamIT, fbFund and Mucker Lab share the same color.

Now let us try to see from the location angle

So we re-established that YC is freaking huge and having them on a chart with other accelerators does not create beautiful visualizations.

Even though there is nothing juicy about Bed bugs but the data about Boston open cases for Bed bugs is quite interesting and worth looking at.

We uploaded the entire 50 mb data dump which is around 500K rows into the Data Visualizer and filtered the category for Bed Bugs. Splitting the date into its date hierarchy components we then plotted the month on the Y axis.

Recently, here at InfoCaptor we started a small research on the subject of flags. We wanted to answer certain questions like what are the most frequently used colors across all country flags, what are the different patterns etc.

The innovation engine in the field of Business Intelligence and Data visualization tools , is certainly cranked up. Qlikview, Tableau and Tibco Spotfire introduced new category of Data Visualization term in the field of Business Intelligence.

Now every vendor offers some form of Data Discovery. Oracle is also working on something similar adding to their confusing mix of OBIEE stack.

With the launch of new InfoCaptor, you can perform ad-hoc data visualizations and build dashboards all within the browser. Now that is refreshing. The browser is the key here. Once you deploy on the server, users can simply login, upload their datasets or point to existing database connection. Before you know users are already slicing and dicing their datasets and swimming in the world of beautiful visualizations. Yes, the visualizations are absolutely stunning and why shouldn’t they be. It is based on the excellent d3js.org library.

The key here is that the browser is your canvas and it is pretty huge, for e.g the detfault size for the visuals takes up my entire browser screen real estate. I like big visuals and if I am producing a Trellis chart then I can simply drag the corners and resize it. The visualization library is very comprehensive and offers around 30 visuals. It provides the bullet graph as well for KPI tracking.

Here are some screenshots from the website

InfoCaptor is also available on the cloud as a service and based on that there are few live analysis to try out without login or installing anything.

I would say with this release small business owners have truly found their Tableau or Qlikview alternative.